Russian team develops machine learning model to predict stability of rare earth and actinide complexes
Researchers from the Interdisciplinary Laboratory for Intelligent Chemical Design at the Department of Chemistry of Lomonosov Moscow State University, in collaboration with colleagues from the Department of Mechanics and Mathematics, have developed a new machine learning model for evaluating the stability of complexes of rare earth elements and trivalent actinides. The results have been published in the Journal of Chemical Physics. The research team stated that machine learning can reduce time and material costs in chemical research, which is particularly important for rare, expensive, or hazardous lanthanides and actinides. Lanthanides, along with scandium and yttrium, are commonly classified as rare earth elements and are widely used in permanent magnets, batteries, electronic components, lasers, and other applications. Since rare earth elements in nature...
2026-08-25
